{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "00059128",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:44.676078Z",
     "iopub.status.busy": "2023-08-31T04:11:44.675906Z",
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    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import os, pathlib\n",
    "from importlib import reload\n",
    "import logging, warnings\n",
    "from scipy.stats import pearsonr\n",
    "logging.basicConfig(level=logging.ERROR)\n",
    "warnings.simplefilter(\"ignore\")\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.decomposition import PCA\n",
    "import scipy.linalg as linalg\n",
    "import matplotlib.pyplot as plt\n",
    "import pyaldata as pyal\n",
    "from typing import Callable\n",
    "\n",
    "if \"__file__\" not in dir():\n",
    "    try:\n",
    "        NBPath = pathlib.Path.cwd()\n",
    "        RepoPath = NBPath.parent\n",
    "        os.chdir(RepoPath)\n",
    "\n",
    "        from tools import utilityTools as utility\n",
    "        from tools import dataTools as dt\n",
    "        from tools import ccaTools as cca\n",
    "        \n",
    "        from tools import lstm\n",
    "        import params\n",
    "        monkey_defs = params.monkey_defs\n",
    "        mouse_defs = params.mouse_defs\n",
    "\n",
    "        set_rc =  params.set_rc_params\n",
    "        set_rc()\n",
    "        root = params.root\n",
    "\n",
    "        os.chdir(RepoPath / 'monkey')\n",
    "        %run \"_dataset-selection.ipynb\"\n",
    "\n",
    "    finally:\n",
    "        os.chdir(NBPath)\n",
    "\n",
    "    print('Done')\n",
    "\n",
    "FIGPATH = params.figPath / 'figS7-topology'\n",
    "if not os.path.exists(FIGPATH):\n",
    "    os.makedirs(FIGPATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e92ff10",
   "metadata": {},
   "source": [
    "### Get data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c14f4bdc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:45.771231Z",
     "iopub.status.busy": "2023-08-31T04:11:45.770805Z",
     "iopub.status.idle": "2023-08-31T04:11:45.780884Z",
     "shell.execute_reply": "2023-08-31T04:11:45.780307Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_time_averaged_data_array(data_list: list[pd.DataFrame], epoch: Callable =None , area: str ='M1', model: Callable =None, n_components:int = 10) -> np.ndarray:\n",
    "    \"\"\"\n",
    "    Applies the `model` to the `data_list` and return a data matrix of the shape: sessions x targets x trials x time x modes\n",
    "    with the minimum number of trials and timepoints shared across all the datasets/targets.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    `data_list`: list of pd.dataFrame datasets from pyalData (could also be a single dataset)\n",
    "    `epoch`: an epoch function of the type `pyal.generate_epoch_fun()`\n",
    "    `area`: area, either: 'M1', or 'S1', or 'PMd', ...\n",
    "    `model`: a model that implements `.fit()`, `.transform()` and `n_components`. By default: `PCA(10)`. If it's an integer: `PCA(integer)`.\n",
    "    `n_components`: use `model`, this is for backward compatibility\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    `AllData`: np.ndarray\n",
    "\n",
    "    Signature\n",
    "    -------\n",
    "    AllData = get_data_array(data_list, execution_epoch, area='M1', model=10)\n",
    "    all_data = np.reshape(AllData, (-1,10))\n",
    "    \"\"\"\n",
    "    if isinstance(data_list, pd.DataFrame):\n",
    "        data_list = [data_list]\n",
    "    \n",
    "    existing_model = False\n",
    "    if model is None:\n",
    "        model = PCA(n_components=n_components, svd_solver='full')\n",
    "    elif isinstance(model, int):\n",
    "        model = PCA(n_components=model, svd_solver='full')\n",
    "    else:\n",
    "        existing_model = True\n",
    "    \n",
    "    field = f'{area}_rates'\n",
    "    n_shared_trial = np.inf\n",
    "    target_ids = np.unique(data_list[0].target_id)\n",
    "    for df in data_list:\n",
    "        for target in target_ids:\n",
    "            df_ = pyal.select_trials(df, df.target_id== target)\n",
    "            n_shared_trial = np.min((df_.shape[0], n_shared_trial))\n",
    "\n",
    "    n_shared_trial = int(n_shared_trial)\n",
    "\n",
    "    # finding the number of timepoints\n",
    "    n_timepoints = 1\n",
    "\n",
    "    # pre-allocating the data matrix\n",
    "    AllData = np.empty((len(data_list), len(target_ids), n_shared_trial, n_timepoints, model.n_components))\n",
    "\n",
    "    rng = np.random.default_rng(12345)\n",
    "    for session, df in enumerate(data_list):\n",
    "        df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
    "        df_[field] = [np.mean(trial, axis = 0) for trial in df_[field]]\n",
    "        rates = np.vstack(df_[field].values)\n",
    "        if existing_model:\n",
    "            rates_model = model\n",
    "        else:\n",
    "            rates_model = model.fit(rates)\n",
    "        df_['_pca'] = [rates_model.transform(s.reshape(1,-1)) for s in df_[field]]\n",
    "\n",
    "        for targetIdx,target in enumerate(target_ids):\n",
    "            df__ = pyal.select_trials(df_, df_.target_id==target)\n",
    "            all_id = df__.trial_id.to_numpy()\n",
    "            # to guarantee shuffled ids\n",
    "            while ((all_id_sh := rng.permutation(all_id)) == all_id).all():\n",
    "                continue\n",
    "            all_id = all_id_sh\n",
    "            # select the right number of trials to each target\n",
    "            df__ = pyal.select_trials(df__, lambda trial: trial.trial_id in all_id[:n_shared_trial])\n",
    "            for trial, trial_rates in enumerate(df__._pca):\n",
    "                AllData[session,targetIdx,trial, :, :] = trial_rates\n",
    "\n",
    "    return AllData"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f5c85bb",
   "metadata": {},
   "source": [
    "### FigS10B: plot topology alignment example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9a13eb99",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:45.783212Z",
     "iopub.status.busy": "2023-08-31T04:11:45.782964Z",
     "iopub.status.idle": "2023-08-31T04:11:45.793329Z",
     "shell.execute_reply": "2023-08-31T04:11:45.792849Z"
    }
   },
   "outputs": [],
   "source": [
    "@utility.report\n",
    "def plot_monkey_topology_ex(azim = None, elev = None):\n",
    "    defs = monkey_defs\n",
    "    # raster_example = defs.raster_example\n",
    "    raster_example = ('Chewie_CO_FF_2016-10-13.p', 'Mihili_CO_FF_2014-02-17.p')\n",
    "    raster_example_df = []\n",
    "    for session in raster_example:\n",
    "        path = root/session.split('_')[0]/session\n",
    "        df = defs.prep_general(dt.load_pyal_data(path))\n",
    "        raster_example_df.append(df)\n",
    "    \n",
    "    df1, df2 = raster_example_df\n",
    "\n",
    "    #get model from df1\n",
    "    model = PCA(n_components=monkey_defs.n_components, svd_solver='full')\n",
    "    field = f'{monkey_defs.areas[2]}_rates'\n",
    "    df_ = pyal.restrict_to_interval(df, epoch_fun=monkey_defs.exec_epoch) \n",
    "    df_[field] = [np.mean(trial, axis = 0) for trial in df_[field]]\n",
    "    rates = np.vstack(df_[field].values)\n",
    "    rates_model = model.fit(rates)\n",
    "\n",
    "    # time-averaged data\n",
    "    AllData1_timeave = get_time_averaged_data_array(df1, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)[0]\n",
    "    AllData2_timeave = get_time_averaged_data_array(df2, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)[0]\n",
    "    AllData2_timeave_fitted = get_time_averaged_data_array(df2, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=rates_model)[0]\n",
    "\n",
    "    _, min_trials, min_time,_ = np.min((AllData1_timeave.shape,AllData2_timeave.shape),axis=0)\n",
    "\n",
    "    #unaligned\n",
    "    data1_timeave = np.reshape(AllData1_timeave[:,:min_trials,:,:], (-1,monkey_defs.n_components))\n",
    "    data2_timeave = np.reshape(AllData2_timeave[:,:min_trials,:,:], (-1,monkey_defs.n_components))\n",
    "\n",
    "    #plotting unaligned\n",
    "    fig=plt.figure(dpi=100)\n",
    "    ax = fig.add_subplot(projection = '3d')\n",
    "    colors = utility.get_colors(8)\n",
    "\n",
    "    for tar in range(8):\n",
    "        ax.scatter(*data1_timeave[(tar)*min_trials:(tar+1)*min_trials, :3].T, edgecolors = colors[tar], marker = 'o', facecolors='none', alpha = 1)\n",
    "        ax.scatter(*data2_timeave[(tar)*min_trials:(tar+1)*min_trials, :3].T, edgecolors = colors[tar], marker = 's', facecolors='none', alpha = 1)\n",
    "    \n",
    "    ax.set_xlabel('Neural mode 1')\n",
    "    ax.set_ylabel('Neural mode 2')\n",
    "    ax.set_zlabel('Neural mode 3')\n",
    "\n",
    "    if elev is not None:\n",
    "        ax.elev = elev\n",
    "    if azim is not None:\n",
    "        ax.azim = azim\n",
    "    plt.savefig(FIGPATH / 'topo_unaligned.pdf', format = 'pdf')\n",
    "\n",
    "    #aligned\n",
    "    A,B,_,U,V = cca.canoncorr(data1_timeave, data2_timeave, fullReturn = True)\n",
    "    U1, _, Vh1 = linalg.svd(A, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False)\n",
    "    U2, _, Vh2 = linalg.svd(B, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False)\n",
    "\n",
    "    #plotting aligned\n",
    "    fig=plt.figure(dpi=100)\n",
    "    ax = fig.add_subplot(projection = '3d')\n",
    "    colors = utility.get_colors(8)\n",
    "\n",
    "    for tar in range(8):\n",
    "        data1_ = data1_timeave[(tar)*min_trials:(tar+1)*min_trials]\n",
    "        data1_ = data1_ @ U1 @ Vh1\n",
    "        ax.scatter(*data1_[:,:3].T, edgecolors = colors[tar], marker = 'o', facecolors='none', alpha = 1)\n",
    "\n",
    "        data2_ = data2_timeave[(tar)*min_trials:(tar+1)*min_trials]\n",
    "        data2_ = data2_ @ U2 @ Vh2\n",
    "        ax.scatter(*data2_[:,:3].T, edgecolors = colors[tar], marker = 's', facecolors='none', alpha = 1)\n",
    "    \n",
    "    ax.set_xlabel('Neural mode 1')\n",
    "    ax.set_ylabel('Neural mode 2')\n",
    "    ax.set_zlabel('Neural mode 3')\n",
    "\n",
    "    if elev is not None:\n",
    "        ax.elev = elev\n",
    "    if azim is not None:\n",
    "        ax.azim = azim\n",
    "    \n",
    "    plt.savefig(FIGPATH / 'topo_aligned_ex.pdf', format = 'pdf')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7dd5fbec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:45.795175Z",
     "iopub.status.busy": "2023-08-31T04:11:45.795014Z",
     "iopub.status.idle": "2023-08-31T04:11:49.415504Z",
     "shell.execute_reply": "2023-08-31T04:11:49.414896Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executed: `plot_monkey_topology_ex` in 3.4s\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %matplotlib widget\n",
    "plot_monkey_topology_ex(azim = -49, elev = 65)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24ba9b91",
   "metadata": {},
   "source": [
    "### Fig S10C&D: CCA based on aligning dynamics vs topology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "55ab4f90-108f-4c22-a744-3a35db5b2038",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:49.418743Z",
     "iopub.status.busy": "2023-08-31T04:11:49.418233Z",
     "iopub.status.idle": "2023-08-31T04:11:49.428573Z",
     "shell.execute_reply": "2023-08-31T04:11:49.428078Z"
    }
   },
   "outputs": [],
   "source": [
    "@utility.report\n",
    "def plot_monkey_topology(ax, full_list_MCx, allDFs_MCx):\n",
    "    pairFileList = dt.get_paired_files_monkey(allDFs_MCx)\n",
    "\n",
    "    side1df = [allDFs_MCx[i] for i,_ in pairFileList]\n",
    "    side2df = [allDFs_MCx[j] for _,j in pairFileList]\n",
    "\n",
    "    # ccs from time-dependent data\n",
    "    AllData1 = dt.get_data_array(side1df, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)\n",
    "    AllData2 = dt.get_data_array(side2df, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)\n",
    "\n",
    "    # time-averaged data\n",
    "    AllData1_timeave = get_time_averaged_data_array(side1df, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)\n",
    "    AllData2_timeave = get_time_averaged_data_array(side2df, monkey_defs.exec_epoch, area=monkey_defs.areas[2], model=monkey_defs.n_components)\n",
    "\n",
    "    _,_, min_trials, min_time,_ = np.min((AllData1.shape,AllData2.shape),axis=0)\n",
    "\n",
    "    allCCs=[]\n",
    "    topoCCs=[]\n",
    "    for sessionData1, sessionData2, sessionData1_timeave, sessionData2_timeave in zip(AllData1, AllData2, AllData1_timeave, AllData2_timeave):\n",
    "\n",
    "        #normal CCs\n",
    "        data1 = np.reshape(sessionData1[:,:min_trials,:min_time,:], (-1,monkey_defs.n_components))\n",
    "        data2 = np.reshape(sessionData2[:,:min_trials,:min_time,:], (-1,monkey_defs.n_components))\n",
    "\n",
    "        r = cca.canoncorr(data1, data2)\n",
    "        allCCs.append(r)\n",
    "     \n",
    "        #topo CCs\n",
    "        data1_timeave = np.reshape(sessionData1_timeave[:,:min_trials,:,:], (-1,monkey_defs.n_components))\n",
    "        data2_timeave = np.reshape(sessionData2_timeave[:,:min_trials,:,:], (-1,monkey_defs.n_components))\n",
    "\n",
    "        A,B,_,U,V = cca.canoncorr(data1_timeave, data2_timeave, fullReturn = True)\n",
    "        \n",
    "        #project normal data into CCs found by time averaged data\n",
    "        n, p1 = data1.shape\n",
    "        X = data1 - np.mean(data1,0);\n",
    "        Y = data2 - np.mean(data2,0);\n",
    "        U = X @ A / np.sqrt(n-1)\n",
    "        V = Y @ B / np.sqrt(n-1)\n",
    "\n",
    "        r = np.array([pearsonr(U_.flatten(), V_.flatten())[0] for U_,V_ in zip(U.T,V.T)])\n",
    "        topoCCs.append(r)\n",
    "\n",
    "    allCCs = np.array(allCCs).T\n",
    "    topoCCs = np.array(topoCCs).T\n",
    "\n",
    "    colors = utility.get_colors(6)\n",
    "    for i, (x, y) in enumerate(zip(allCCs[:6,], topoCCs[:6,])):\n",
    "        ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
    "\n",
    "    ymin, ymax = ax.get_ylim()\n",
    "    ax.set_xlim((ymin,1))\n",
    "    ax.set_ylim((ymin,1))\n",
    "    ax.set_aspect(1)\n",
    "    ax.plot([ymin, 1], [ymin,1], c = 'grey')\n",
    "    ax.set_ylabel('Corr. aligning topology')\n",
    "    ax.set_xlabel('Corr. aligning dynamics')\n",
    "    ax.legend()\n",
    "    \n",
    "    return allCCs, topoCCs\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c6d8e701-2e04-41c4-bc4c-2383ef0badd5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:11:49.430597Z",
     "iopub.status.busy": "2023-08-31T04:11:49.430364Z",
     "iopub.status.idle": "2023-08-31T04:14:36.476327Z",
     "shell.execute_reply": "2023-08-31T04:14:36.476004Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running: `plot_monkey_topology`...\r"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/home/jcc319/multi_animal_alignment/tools/dataTools.py:129: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/239038360.py:52: UserWarning: Dropping the trials with the following IDs because of invalid time indexing. For more information, try warn_per_trial=True\n",
      "\n",
      "        [1157]\n",
      "  df_ = pyal.restrict_to_interval(df, epoch_fun=epoch) if epoch is not None else df\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n",
      "/tmp/ipykernel_29621/1873331828.py:50: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "  ax.scatter(x.flatten(),y.flatten(), c = colors[i], label = f'{i+1}')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executed: `plot_monkey_topology` in 146.6s\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(dpi=100)\n",
    "ax = fig.add_subplot()\n",
    "\n",
    "full_list_MCx, allDFs_MCx = dt.get_full_monkey_data(GoodDataList_CO)\n",
    "\n",
    "allCCs, topoCCs = plot_monkey_topology(ax, full_list_MCx, allDFs_MCx)\n",
    "plt.savefig(FIGPATH / 'topo_vs_dynamics.pdf', format = 'pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5f0cc125",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-31T04:14:36.477840Z",
     "iopub.status.busy": "2023-08-31T04:14:36.477703Z",
     "iopub.status.idle": "2023-08-31T04:14:36.842789Z",
     "shell.execute_reply": "2023-08-31T04:14:36.842470Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.linspace(-1, 1, 40)\n",
    "fig=plt.figure(dpi=100)\n",
    "ax = fig.add_subplot()\n",
    "ax.hist(np.mean(allCCs[:4,],0).flatten(), bins = bins, label = 'Dynamics', color = 'k')\n",
    "ax.hist(np.mean(topoCCs[:4,],0).flatten(), bins = bins, label = 'Topology', color = 'grey')\n",
    "ax.legend()\n",
    "ax.set_xlabel('Correlation')\n",
    "plt.savefig(FIGPATH / 'topo_vs_dynamics_hist.pdf', format = 'pdf')"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f438ab41c639bccf4a0690d593feedbc6f327eadb4a78567565a57c35fedcdae"
  },
  "kernelspec": {
   "display_name": "Python 3.10.5 ('cca': conda)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
    "hash": "146bff742f048d001dec7fafb91c8daeb769f9aeaad9c8d129a83c9f9fb9a9b2"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
